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17 lines
1.4 KiB
Markdown
17 lines
1.4 KiB
Markdown
---
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name: dgx-spark-nemo-fine-tune
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description: Use NVIDIA NeMo to fine-tune models locally — on NVIDIA DGX Spark. Use when setting up nemo-fine-tune on Spark hardware.
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---
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<!-- GENERATED:BEGIN from nvidia/nemo-fine-tune/README.md -->
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# Fine-tune with NeMo
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> Use NVIDIA NeMo to fine-tune models locally
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This playbook guides you through setting up and using NVIDIA NeMo AutoModel for fine-tuning large language models and vision-language models on NVIDIA Spark devices. NeMo AutoModel provides GPU-accelerated, end-to-end training for Hugging Face models with native PyTorch support, enabling instant fine-tuning without conversion delays. The framework supports distributed training across single GPU to multi-node clusters, with optimized kernels and memory-efficient recipes specifically designed for ARM64 architecture and Blackwell GPU systems.
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**Outcome**: You'll establish a complete fine-tuning environment for large language models (1-70B parameters) and vision-language models using NeMo AutoModel on your NVIDIA Spark device. By the end, you'll have a working installation that supports parameter-efficient fine-tuning (PEFT), supervised fine-tuning (SFT), and distributed training capabilities with FP8 precision optimizations, all while maintaining compatibility with the Hugging Face ecosystem.
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**Full playbook**: `/home/runner/work/dgx-spark-playbooks/dgx-spark-playbooks/nvidia/nemo-fine-tune/README.md`
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<!-- GENERATED:END -->
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